机器人外科学杂志（中英文）2024，Vol.5Issue(2)：121-129,9.DOI:10.12180/j.issn.2096-7721.2024.02.002
基于递归神经网络的人体下肢运动意图识别方法
A motion intention recognition method of human lower limbs based on recurrent neural network
摘要
Abstract
In order to accurately identify the active motion intention of human lower limbs,the surface electromyography(sEMG)signals of the two channels and the corresponding joint motion information were collected,and the raw sEMG signals were preprocessed.Then an open-loop prediction model based on radial basis function neural network was established,using the preprocessed sEMG signal as the input and the joint motion information as the output.On this basis,as a special recurrent neural network,the zeroing neural network was exploited to the open-loop model to form a hybrid closed-loop prediction model.The experimental results indicated that the proposed closed-loop model can effectively eliminate the prediction error of the open-loop model,and it can more accurately identify the active motion intention of human lower limbs,which lays a reliable foundation for the subsequent human-computer interaction system of the rehabilitation robot.关键词
表面肌电信号/主动运动/运动意图/下肢/归零神经网络/径向基函数神经网络Key words
Surface Electromyography(sEMG)/Active Motion/Motion Intention/Lower Limbs/Zeroing Neural Network/Radial Basis Function Neural Network分类
信息技术与安全科学引用本文复制引用
张鑫,李婉婷,陈岩,孙中波..基于递归神经网络的人体下肢运动意图识别方法[J].机器人外科学杂志（中英文）,2024,5(2):121-129,9.基金项目
国家自然科学基金面上项目(61873304,62173048) （61873304,62173048）
吉林省教育厅科学研究项目(JJKH20210745KJ) National Natural Science Foundation of China(61873304,62173048) （JJKH20210745KJ）
Scientific Research Project of Department of Education of Jilin Province(JJKH20210745KJ) （JJKH20210745KJ）
